Primates en Costa Rica

Carga de paquetes

library(sf)
library(raster)
library(dplyr)
library(spData)

library(leaflet)
library(plotly)
library(DT)
library(RColorBrewer)

Conjunto de datos

# Especies de primates en Costa Rica
Primates <- st_read("https://raw.githubusercontent.com/gf0604-procesamientodatosgeograficos/2021i-datos/main/gbif/primates-cr-registros.csv",
                    options = c("X_POSSIBLE_NAMES=decimalLongitude",
                                "Y_POSSIBLE_NAMES=decimalLatitude"),
                    quiet = TRUE)

# Capa de cantones

Cantones <- st_read("https://raw.githubusercontent.com/gf0604-procesamientodatosgeograficos/2021i-datos/main/ign/delimitacion-territorial-administrativa/cr_cantones_simp_wgs84.geojson",
                    quiet = TRUE)

# crs 

st_crs(Primates) = 4326

# Cruce espacial con los datos de los cantones 

Primates <- Primates %>% 
  st_join(Cantones["canton"])

rownames = FALSE 
options = list(
  searchHighlight = TRUE, 
  language = list(url = "//cdn.datatables.net/plug-ins/1.10.11/i18n/spanish.json"), 
  pageLength = 5)

Primera parte

Tabla con el registro de las especies de primates en Costa Rica

Primates %>%
  st_drop_geometry() %>%
  select(family, species, stateProvince, canton, eventDate) %>%
  datatable(colnames = c("Familia", 
                         "Especie",
                         "Provincia",
                         "Cantón",
                         "Fecha")
            )

            options = list(searchHighlight = TRUE,
            language = list(url = "//cdn.datatables.net/plug-ins/1.10.11/i18n/spanish.json")
            )

Segunda parte

g <- data.frame("Categorie" = rownames(Primates), Primates)

g1 <- g[, c("Categorie", "species", "recordNumber")]

color <- brewer.pal(length(count), "PiYG")

## Warning in brewer.pal(length(count), "PiYG"): minimal value for n is 3, returning requested palette with 3 different levels

Gráfico de pastel con cada una de las especies en Costa Rica

plot_ly(g1,
        labels = ~ species, 
        type = "pie"
        ) %>%
  layout(
    title = "Registros para las especie y el porcentaje total que representa cada una de estas", 
    xaxis = list(
      showgrid = FALSE,
      zeroline = FALSE, 
      showticklabels = FALSE
      
    ),
    yaxis = list(
      showgrid = FALSE,
      zeroline = FALSE, 
      showticklabels = FALSE
    )
    
  )

Tercera parte

Crear variables

AG <- Primates %>% 
  filter(species == "Ateles geoffroyi")

CC <- Primates %>%
  filter(species == "Cebus capucinus")

AP <- Primates %>%
  filter(species == "Alouatta palliata")

SO <- Primates %>% 
  filter(species == "Saimiri oerstedii")

Mapa de la presencia de primates

Primates %>%
  select(stateProvince,
         canton,
         eventDate,
         species) %>%
  leaflet() %>%
  addProviderTiles(providers$OpenStreetMap.Mapnik, group = "OpenStreetMap") %>%
  addProviderTiles(providers$Stamen.Tonerlite, group = "Stamen Toner Life") %>%
  addProviderTiles(providers$Esri.WorldImagery, group = "Imágenes de ESRI") %>%
  addCircleMarkers(
    data = AG,
    stroke = F,
    radius = 4,
    fillColor = "red",
    fillOpacity = 2,
    popup = paste(
      Primates$stateProvince,
      Primates$canton,
      Primates$eventDate,
      Primates$species,
      sep = "<br/>"
    ),
    group = "AG"
  )%>%
  
  addCircleMarkers(
    data = CC,
    stroke = F,
    radius = 4,
    fillColor = "blue",
    fillOpacity = 2,
    popup = paste(
      Primates$stateProvince,
      Primates$canton,
      Primates$eventDate,
      Primates$species,
      sep = "<br/>"
    ),
    group = "CC"
) %>%
  
  
    addCircleMarkers(
    data = AP,
    stroke = F,
    radius = 4,
    fillColor = "aqua marine",
    fillOpacity = 2,
    popup = paste(
      Primates$stateProvince,
      Primates$canton,
      Primates$eventDate,
      Primates$species,
      sep = "<br/>"
    ),
    group = "AP"
) %>%
  
    addCircleMarkers(
    data = SO,
    stroke = F,
    radius = 4,
    fillColor = "green",
    fillOpacity = 2,
    popup = paste(
      Primates$stateProvince,
      Primates$canton,
      Primates$eventDate,
      Primates$species,
      sep = "<br/>"
    ),
    group = "SO"
) %>%

  addLayersControl(
    baseGroups = c("OpenStreetMap", "Stamen Toner Lite", "Imágenes de ESRI"),
    overlayGroups = c("Primates")
  ) %>%
  addMiniMap(
    tiles = providers$Stamen.OpenStreetMap.Mapnik,
    position = "bottomleft",
    toggleDisplay = TRUE
  )